scholarly journals Evaluating the Climate Effects of Reforestation in New England Using a Weather Research and Forecasting (WRF) Model Multiphysics Ensemble

2016 ◽  
Vol 29 (14) ◽  
pp. 5141-5156 ◽  
Author(s):  
E. A. Burakowski ◽  
S. V. Ollinger ◽  
G. B. Bonan ◽  
C. P. Wake ◽  
J. E. Dibb ◽  
...  
Keyword(s):  
Heat Flux ◽  
New England ◽  
Sensible Heat Flux ◽  
Climate Impacts ◽  
Maximum Temperature ◽  
Weather Research And Forecasting ◽  
Surface Model ◽  
Sensible Heat ◽  
Ground Heat Flux ◽  
Weather Research

Abstract The New England region of the northeastern United States has a land use history characterized by forest clearing for agriculture and other uses during European colonization and subsequent reforestation following widespread farm abandonment. Despite these broad changes, the potential influence on local and regional climate has received relatively little attention. This study investigated wintertime (December through March) climate impacts of reforestation in New England using a high-resolution (4 km) multiphysics ensemble of the Weather Research and Forecasting Model. In general, the conversion from mid-1800s cropland/grassland to forest led to warming, but results were sensitive to physics parameterizations. The 2-m maximum temperature (T2max) was most sensitive to choice of land surface model, 2-m minimum temperature (T2min) was sensitive to radiation scheme, and all ensemble members simulated precipitation poorly. Reforestation experiments suggest that conversion of mid-1800s cropland/grassland to present-day forest warmed T2max +0.5 to +3 K, with weaker warming during a warm, dry winter compared to a cold, snowy winter. Warmer T2max over forests was primarily the result of increased absorbed shortwave radiation and increased sensible heat flux compared to cropland/grassland. At night, T2min warmed +0.2 to +1.5 K where deciduous broadleaf forest replaced cropland/grassland, a result of decreased ground heat flux. By contrast, T2min of evergreen needleleaf forest cooled –0.5 to –2.1 K, primarily owing to increased ground heat flux and decreased sensible heat flux.

scholarly journals Investigating the Effect of Urbanization on Weather Using the Weather Research and Forecasting (WRF) Model: A Case of Metro Manila, Philippines

Environments ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 10 ◽  
Author(s):  
Jervie Oliveros ◽  
Edgar Vallar ◽  
Maria Galvez
Keyword(s):  
Heat Flux ◽  
Rural Areas ◽  
Sensible Heat Flux ◽  
Maximum Temperature ◽  
Weather Research And Forecasting ◽  
Trend Test ◽  
Sensible Heat ◽  
Metro Manila ◽  
Urban And Rural Areas ◽  
Weather Research

The effect of urbanization of Metro Manila, particularly on the amount of sensible heat flux, rainfall and temperature of selected urban and rural areas, was investigated using the Weather Research and Forecasting Version 3.4.1 (WRFV3.4.1) model. National Center for Environmental Prediction - Final (NCEP-FNL) grib1 data from 2000 to 2010 were used as inputs into the model for meteorological data. The Mann–Kendall trend test (M–K test) was utilized to verify the significance of the trends while Sen’s slope estimator was used to quantify the measured trends. Results showed that, on average, the sensible heat flux of Metro Manila is about 1.5 × 108 Jm−2 higher than in selected areas outside Metro Manila. The occurrence of an urban heat island (UHI) effect was detected in Metro Manila by comparing the difference in the minimum and maximum temperatures. For the selected urban and rural areas, the minimum and maximum temperature differences (relative to Metro Manila) are around 0.4 to 2.4 °C and 0.83 to 2.3 °C, respectively. Metro Manila recorded higher 11-year average values of rainfall during the summer season (8% to 64%), rainy season (15% to 305%), and transition season (8% to 232%) when compared with selected areas from 25 to 100 km from Manila. These results show that the sensible heat flux, temperature and rainfall in Metro Manila is affected by Metro Manila’s urbanization.

scholarly journals Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models

2010 ◽  
Vol 11 (5) ◽  
pp. 1103-1122 ◽  
Author(s):  
Rolf H. Reichle ◽  
Sujay V. Kumar ◽  
Sarith P. P. Mahanama ◽  
Randal D. Koster ◽  
Q. Liu
Keyword(s):  
Heat Flux ◽  
Data Assimilation ◽  
Skin Temperature ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Land Surface Model ◽  
Open Loop ◽  
Surface Model ◽  
Ground Heat Flux ◽  
Assimilation System

Abstract Land surface (or “skin”) temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research LST retrievals from the International Satellite Cloud Climatology Project (ISCCP) are assimilated into the Noah land surface model and Catchment land surface model (CLSM) using an ensemble-based, offline land data assimilation system. LST is described very differently in the two models. A priori scaling and dynamic bias estimation approaches are applied because satellite and model LSTs typically exhibit different mean values and variabilities. Performance is measured against 27 months of in situ measurements from the Coordinated Energy and Water Cycle Observations Project at 48 stations. LST estimates from Noah and CLSM without data assimilation (“open loop”) are comparable to each other and superior to ISCCP retrievals. For LST, the RMSE values are 4.9 K (CLSM), 5.5 K (Noah), and 7.6 K (ISCCP), and the anomaly correlation coefficients (R) are 0.61 (CLSM), 0.63 (Noah), and 0.52 (ISCCP). Assimilation of ISCCP retrievals provides modest yet statistically significant improvements (over an open loop, as indicated by nonoverlapping 95% confidence intervals) of up to 0.7 K in RMSE and 0.05 in the anomaly R. The skill of the latent and sensible heat flux estimates from the assimilation integrations is essentially identical to the corresponding open loop skill. Noah assimilation estimates of ground heat flux, however, can be significantly worse than open loop estimates. Provided the assimilation system is properly adapted to each land model, the benefits from the assimilation of LST retrievals are comparable for both models.

scholarly journals Study of energy balance components at different growth stages of green gram grown in new alluvial zone of West Bengal

MAUSAM ◽  
2021 ◽  
Vol 71 (2) ◽  
pp. 315-320
Author(s):  
MONDAL SOUMEN ◽  
BANERJEE SAON ◽  
CHAKRABORTY SHAON ◽  
SAHA SALIL ◽  
MUKHERJEE ASIS
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
West Bengal ◽  
Sensible Heat Flux ◽  
Bowen Ratio ◽  
Green Gram ◽  
Growth Stages ◽  
Sensible Heat ◽  
Net Radiation ◽  
Ground Heat Flux

An experiment was conducted in the experimental farm of Bidhan Chandra KrishiViswavidyalaya, Nadia, West Bengal to study the radiation pattern and its balance over green gram (Vignaradiata var. Samrat). The BREB method was used to determine the sensible heat flux and latent energy. The net radiation was measured through net radiometer and the ground heat flux was measured using Fourier's law. Both the diurnal and seasonal variation of net radiation were studied. Similarly, the energy balance components were studied regularly for different crop growth stages as well as on diurnal basis. It is observed that the net radiation varies from 6.32 Wm-2 to 606.43 Wm-2. The latent heat flux constitutes more than 50% of the net radiation for all growth stages as depicted by energy balance partitioning. The sensible heat flux is partitioned into 10% to 20% of total net radiation throughout the growth stages of green gram, which is the lowest in magnitude among all three energy fluxes. The relationship between Bowen ratio and Vapour pressure deficit (VPD), Bowen ratio and Canopy air temperature difference (CATD) was studied. It was found that Bowen ratio is negatively correlated with VPD but positively correlated with CATD. This study enables to monitor ET pattern through latent heat flux and microclimatic characteristics through sensible and ground heat flux.

scholarly journals A New Land-Use Dataset for the Weather Research and Forecasting (WRF) Model

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 350
Author(s):  
Huoqing Li ◽  
Hailiang Zhang ◽  
Ali Mamtimin ◽  
Shuiyong Fan ◽  
Chenxiang Ju
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Northwest China ◽  
Specific Humidity ◽  
Weather Research And Forecasting ◽  
United States Geological Survey ◽  
Parameter Values ◽  
Weather Research

The USGS (United States Geological Survey) land-use data used in the Weather Research and Forecasting (WRF) model have become obsolete as they are unable to accurately represent actual underlying surface features. Therefore, this study developed a new multi-satellite remote-sensing land-use dataset based on the latest GLC2015 (Global Land Cover, 2015) land-use data, which had 300 m spatial resolution. The new data were used to update the default USGS land-use dataset. Based on observational data from national meteorological observing stations in Xinjiang, northwest China, a comparison of the old USGS and new GLC2015 land-use datasets in the WRF model was performed for July 2018, where the simulated variables included the sensible heat flux (SHF), latent heat flux (LHF), surface skin temperature (Tsk), two-meter air temperature (T2), wind speed (Winds), specific humidity (Q2) and relative humidity (RH). The results indicated that there were significant differences between the two datasets. For example, our statistical verification results found via in situ observations made by the MET (model evaluation tools) illustrated that the bias of T2 decreased by 2.54%, the root mean square error (RMSE) decreased by 1.48%, the bias of Winds decreased by 10.46%, and the RMSE decreased by 6.77% when using the new dataset, and the new parameter values performed a net positive effect on land–atmosphere interactions. These results suggested that the GLC2015 land-use dataset developed in this study was useful in terms of improving the performance of the WRF model in the summer months.

scholarly journals The efficiency of the Weather Research and Forecasting (WRF) model for simulating typhoons

2014 ◽  
Vol 14 (8) ◽  
pp. 2179-2187 ◽  
Author(s):  
T. Haghroosta ◽  
W. R. Ismail ◽  
P. Ghafarian ◽  
S. M. Barekati
Keyword(s):  
Heat Flux ◽  
Wind Speed ◽  
Model Simulation ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Data Set ◽  
Wind Speed Prediction ◽  
Weather Research

Abstract. The Weather Research and Forecasting (WRF) model includes various configuration options related to physics parameters, which can affect the performance of the model. In this study, numerical experiments were conducted to determine the best combination of physics parameterization schemes for the simulation of sea surface temperatures, latent heat flux, sensible heat flux, precipitation rate, and wind speed that characterized typhoons. Through these experiments, several physics parameterization options within the Weather Research and Forecasting (WRF) model were exhaustively tested for typhoon Noul, which originated in the South China Sea in November 2008. The model domain consisted of one coarse domain and one nested domain. The resolution of the coarse domain was 30 km, and that of the nested domain was 10 km. In this study, model simulation results were compared with the Climate Forecast System Reanalysis (CFSR) data set. Comparisons between predicted and control data were made through the use of standard statistical measurements. The results facilitated the determination of the best combination of options suitable for predicting each physics parameter. Then, the suggested best combinations were examined for seven other typhoons and the solutions were confirmed. Finally, the best combination was compared with other introduced combinations for wind-speed prediction for typhoon Washi in 2011. The contribution of this study is to have attention to the heat fluxes besides the other parameters. The outcomes showed that the suggested combinations are comparable with the ones in the literature.

scholarly journals Urban Energy Fluxes in Built-Up Downtown Areas and Variations across the Urban Area, for Use in Dispersion Models

2011 ◽  
Vol 50 (6) ◽  
pp. 1341-1353 ◽  
Author(s):  
Steven Hanna ◽  
Edson Marciotto ◽  
Rex Britter
Keyword(s):  
Heat Flux ◽  
Rural Areas ◽  
Sensible Heat Flux ◽  
Tall Buildings ◽  
Heat Fluxes ◽  
Sensible Heat ◽  
Dispersion Models ◽  
Energy Fluxes ◽  
Downtown Area ◽  
Ground Heat Flux

AbstractSurface energy fluxes, at averaging times from 10 min to 1 h, are needed as inputs to most state-of-the-art dispersion models. The sensible heat flux is a major priority, because it is combined with the momentum flux to estimate the stability, the wind profile, and the turbulence intensities. Because of recent concerns about dispersion in built-up downtown areas of large cities, there is a need to estimate sensible heat flux in the midst of tall buildings. In this paper, the authors work with some high-quality and relevant but arguably underutilized data. The results of analysis of urban heat flux components from 10 locations in suburban and built-up downtown areas in Oklahoma City, Oklahoma, during the Joint Urban 2003 (JU2003) field experiment are presented here. At street level in the downtown area, in the midst of tall skyscrapers, the ground heat flux and the sensible heat flux are relatively large and the latent heat flux is relatively small when compared with concurrent fluxes observed in the upwind suburban areas. In confirmation of measurements in other cities, the sensible heat flux in the downtown area is observed to be slightly positive (10–20 W m−2) at night, indicating nearly neutral or slightly unstable conditions. Also in agreement with observations in other cities is that the ground heat flux in the downtown area has a magnitude that is 3 or 4 times that in suburban or rural areas. These results should permit improved parameterizations of sensible heat fluxes in the urban downtown area with tall buildings.

scholarly journals The annual surface energy budget of a high-arctic permafrost site on Svalbard, Norway

2009 ◽  
Vol 3 (2) ◽  
pp. 245-263 ◽  
Author(s):  
S. Westermann ◽  
J. Lüers ◽  
M. Langer ◽  
K. Piel ◽  
J. Boike
Keyword(s):  
Heat Flux ◽  
Surface Energy ◽  
Latent Heat ◽  
Energy Budget ◽  
Sensible Heat Flux ◽  
Surface Energy Budget ◽  
Wave Radiation ◽  
Sensible Heat ◽  
Near Surface ◽  
Ground Heat Flux

Abstract. Independent measurements of radiation, sensible and latent heat fluxes and the ground heat flux are used to describe the annual cycle of the surface energy budget at a high-arctic permafrost site on Svalbard. During summer, the net short-wave radiation is the dominant energy source, while well developed turbulent processes and the heat flux in the ground lead to a cooling of the surface. About 15% of the net radiation is consumed by the seasonal thawing of the active layer in July and August. The Bowen ratio is found to vary between 0.25 and 2, depending on water content of the uppermost soil layer. During the polar night in winter, the net long-wave radiation is the dominant energy loss channel for the surface, which is mainly compensated by the sensible heat flux and, to a lesser extent, by the ground heat flux, which originates from the refreezing of the active layer. The average annual sensible heat flux of −6.9 Wm−2 is composed of strong positive fluxes in July and August, while negative fluxes dominate during the rest of the year. With 6.8 Wm−2, the latent heat flux more or less compensates the sensible heat flux in the annual average. Strong evaporation occurs during the snow melt period and particularly during the snow-free period in summer and fall. When the ground is covered by snow, latent heat fluxes through sublimation of snow are recorded, but are insignificant for the average surface energy budget. The near-surface atmospheric stratification is found to be predominantly unstable to neutral, when the ground is snow-free, and stable to neutral for snow-covered ground. Due to long-lasting near-surface inversions in winter, an average temperature difference of approximately 3 K exists between the air temperature at 10 m height and the surface temperature of the snow. As such comprehensive data sets are sparse for the Arctic, they are of great value to improve process understanding and support modeling efforts on the present-day and future arctic climate and permafrost conditions.

scholarly journals Quantifying the uncertainty in estimates of surface- atmosphere fluxes through joint evaluation of the SEBS and SCOPE models

2011 ◽  
Vol 8 (2) ◽  
pp. 2861-2893 ◽  
Author(s):  
J. Timmermans ◽  
C. van der Tol ◽  
A. Verhoef ◽  
W. Verhoef ◽  
Z. Su ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Latent Heat ◽  
Sensible Heat Flux ◽  
Roughness Height ◽  
Accurate Estimation ◽  
Sensible Heat ◽  
Ground Heat Flux ◽  
Scope Model

Abstract. Accurate estimation of global evapotranspiration is considered of great importance due to its key role in the terrestrial and atmospheric water budget. Global estimation of evapotranspiration on the basis of observational data can only be achieved by using remote sensing. Several algorithms have been developed that are capable of estimating the daily evapotranspiration from remote sensing data. Evaluation of remote sensing algorithms in general is problematic because of differences in spatial and temporal resolutions between remote sensing observations and field measurements. This problem can be solved by using Soil Vegetation Atmosphere Transfer (SVAT) models, because on the one hand these models provide evapotranspiration estimations also under cloudy conditions and on the other hand can scale between different spatial resolutions. In this paper, the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model is used for the evaluation of the Surface Energy Balance System (SEBS) model. SCOPE was employed to simulate remote sensing observations and to act as a validation tool. The advantages of the SCOPE model in this validation are (a) the temporal continuity of the data, and (b) the possibility of comparing different components of the energy balance. The SCOPE model was run using data from a whole growth season of a maize crop. It is shown that the original SEBS algorithm produces significant uncertainties in the turbulent flux estimations due to the misparameterizations of the ground heat flux and sensible heat flux. In the original SEBS formulation the fractional vegetation cover is used to calculate the ground heat flux. As this variable saturates very fast for increasing LAI, the ground heat flux is underestimated. It is shown that a parameterization based on LAI greatly reduces the estimation error over the season from RMSE = 25 W m−2 to RMSE = 18 W m−2. The uncertainties in the sensible heat flux arise due to a misparameterization of the roughness height for heat. In the original SEBS formulation the roughness height for heat is only valid for short vegetation. An additional parameterization for tall vegetation was implemented in the SEBS algorithm to correct for this. This improved the correlation between the latent heat flux predicted by the SEBS and the SCOPE algorithm from −0.05 to 0.69, and led to a decrease in error from 123 W m−2 to 94 W m−2 for the latent heat, with SEBS latent heat being consistently lower than the SCOPE reference. In addition the stability of the evaporative fraction was investigated.

scholarly journals Improved parameterization of snow albedo in Noah coupled with Weather Research and Forecasting: applicability to snow estimates for the Tibetan Plateau

2021 ◽  
Vol 25 (9) ◽  
pp. 4967-4981
Author(s):  
Lian Liu ◽  
Yaoming Ma ◽  
Massimo Menenti ◽  
Rongmingzhu Su ◽  
Nan Yao ◽  
...  
Keyword(s):  
Heat Flux ◽  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Snow Depth ◽  
Sensible Heat Flux ◽  
Weather Research And Forecasting ◽  
The Tibetan Plateau ◽  
Sensible Heat ◽  
Snow Albedo

Abstract. Snow albedo is important to the land surface energy balance and to the water cycle. During snowfall and subsequent snowmelt, snow albedo is usually parameterized as functions of snow-related variables in land surface models. However, the default snow albedo scheme in the widely used Noah land surface model shows evident shortcomings in land–atmosphere interaction estimates during snow events on the Tibetan Plateau. Here, we demonstrate that our improved snow albedo scheme performs well after including snow depth as an additional factor. By coupling the Weather Research and Forecasting (WRF) and Noah models, this study comprehensively evaluates the performance of the improved snow albedo scheme in simulating eight snow events on the Tibetan Plateau. The modeling results are compared with WRF run with the default Noah scheme and in situ observations. The improved snow albedo scheme significantly outperforms the default Noah scheme in relation to air temperature, albedo and sensible heat flux estimates by alleviating cold bias estimates, albedo overestimates and sensible heat flux underestimates, respectively. This in turn contributes to more accurate reproductions of snow event evolution. The averaged root mean square error (RMSE) relative reductions (and relative increase in correlation coefficients) for air temperature, albedo, sensible heat flux and snow depth reach 27 % (5 %), 32 % (69 %), 13 % (17 %) and 21 % (108 %), respectively. These results demonstrate the strong potential of our improved snow albedo parameterization scheme for snow event simulations on the Tibetan Plateau. Our study provides a theoretical reference for researchers committed to further improving the snow albedo parameterization scheme.

scholarly journals The annual surface energy budget of a high-arctic permafrost site on Svalbard, Norway

2009 ◽  
Vol 3 (2) ◽  
pp. 631-680 ◽  
Author(s):  
S. Westermann ◽  
J. Lüers ◽  
M. Langer ◽  
K. Piel ◽  
J. Boike
Keyword(s):  
Heat Flux ◽  
Surface Energy ◽  
Latent Heat ◽  
Energy Budget ◽  
Sensible Heat Flux ◽  
Surface Energy Budget ◽  
Wave Radiation ◽  
Sensible Heat ◽  
Near Surface ◽  
Ground Heat Flux

Abstract. Independent measurements of radiation, sensible and latent heat fluxes and the ground heat flux are used to describe the annual cycle of the surface energy budget at a high-arctic permafrost site on Svalbard. During summer, the net short-wave radiation is the dominant energy source, while well developed turbulent processes and the heat flux in the ground lead to a cooling of the surface. About 15% of the net radiation is consumed by the seasonal thawing of the active layer in July and August. The Bowen ratio is found to vary between 0.25 and 2, depending on water content of the uppermost soil layer. During the polar night in winter, the net long-wave radiation is the dominant energy loss channel for the surface, which is mainly compensated by the sensible heat flux and, to a lesser extent, by the ground heat flux, which originates from the refreezing of the active layer. The average annual sensible heat flux of −6.9 Wm−2 is composed of strong positive fluxes in July and August, while negative fluxes dominate during the rest of the year. With 6.8 Wm−2, the latent heat flux more or less compensates the sensible heat flux in the annual average. Strong evaporation occurs during the snow melt period and particularly during the snow-free period in summer and fall. When the ground is covered by snow, latent heat fluxes through sublimation of snow are recorded, but are insignificant for the average surface energy budget. The near-surface atmospheric stratification is found to be predominantly unstable to neutral, when the ground is snow-free, and stable to neutral for snow-covered ground. Due to long-lasting near-surface inversions in winter, an average temperature difference of approximately 3 K exists between the air temperature at 10 m height and the surface temperature of the snow.

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